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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 周承復(Cheng-Fu Chou) | |
dc.contributor.author | Yu-Hsin Liu | en |
dc.contributor.author | 劉雨鑫 | zh_TW |
dc.date.accessioned | 2021-06-15T16:32:40Z | - |
dc.date.available | 2015-08-16 | |
dc.date.copyright | 2015-08-16 | |
dc.date.issued | 2015 | |
dc.date.submitted | 2015-08-13 | |
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[2] Jeffrey Dean and Sanjay Ghemawat. Mapreduce: simplified data processing on large clusters. Communications of the ACM, 51. [3] Yang-hua Chu, Sanjay G Rao, and Hui Zhang. A case for end system multicast (keynote address). In ACM SIGMETRICS Performance Evaluation Review, volume 28, pages 1–12. ACM, 2000. [4] The Age of Big Data, [online] http://www.nytimes.com/2012/02/12/ sunday-review/big-datas-impact-in-the-world.html. [5] Andrea Bianco, Paolo Giaccone, Enrico Maria Giraudo, Fabio Neri, and Enrico Schiattarella. Nxg07-3: Multicast support for a storage area network switch. In Global Telecommunications Conference, 2006. GLOBECOM’06. IEEE, pages 1–6. IEEE, 2006. [6] Abderrahim Benslimane. Multimedia multicast on the internet. John Wiley & Sons, 2013. [7] Amrit Iyer, Pranaw Kumar, and Vijay Mann. Avalanche: data center multicast using software defined networking. In Communication Systems and Networks (COMSNETS), 2014 Sixth International Conference on, pages 1–8. IEEE, 2014. [8] Nick McKeown. Software-defined networking. INFOCOM keynote talk, 17(2):30– 32, 2009. 29 [9] Open Networking Fundation. Software-defined networking: The new norm for networks. ONF White Paper, 2012. [10] Nick McKeown, Tom Anderson, Hari Balakrishnan, Guru Parulkar, Larry Peterson, Jennifer Rexford, Scott Shenker, and Jonathan Turner. Openflow: enabling innovation in campus networks. ACM SIGCOMM Computer Communication Review, 38(2):69–74, 2008. [11] Sankalp Agarwal, Murali Kodialam, and TV Lakshman. Traffic engineering in software defined networks. In INFOCOM, 2013 Proceedings IEEE, pages 2211–2219. IEEE, 2013. [12] Sushant Jain, Alok Kumar, Subhasree Mandal, Joon Ong, Leon Poutievski, Arjun Singh, Subbaiah Venkata, Jim Wanderer, Junlan Zhou, Min Zhu, et al. B4: Experience with a globally-deployed software defined wan. In ACM SIGCOMM Computer Communication Review, volume 43, pages 3–14. ACM, 2013. [13] Chuanxiong Guo, Haitao Wu, Kun Tan, Lei Shi, Yongguang Zhang, and Songwu Lu. Dcell: a scalable and fault-tolerant network structure for data centers. ACM SIGCOMM Computer Communication Review, 38(4):75–86, 2008. [14] Chuanxiong Guo, Guohan Lu, Dan Li, Haitao Wu, Xuan Zhang, Yunfeng Shi, Chen Tian, Yongguang Zhang, and Songwu Lu. Bcube: a high performance, server-centric network architecture for modular data centers. ACM SIGCOMM Computer Communication Review, 39(4):63–74, 2009. [15] Radhika Niranjan Mysore, Andreas Pamboris, Nathan Farrington, Nelson Huang, Pardis Miri, Sivasankar Radhakrishnan, Vikram Subramanya, and Amin Vahdat. Portland: a scalable fault-tolerant layer 2 data center network fabric. In ACM SIGCOMM Computer Communication Review, volume 39, pages 39–50. ACM, 2009. [16] Mohammad Al-Fares, Alexander Loukissas, and Amin Vahdat. A scalable, commodity data center network architecture. ACM SIGCOMM Computer Communication Review, 38(4):63–74, 2008. 30 [17] Dino Farinacci, C Liu, S Deering, D Estrin, M Handley, Van Jacobson, L Wei, Puneet Sharma, David Thaler, and A Helmy. Protocol independent multicast-sparse mode (pim-sm): Protocol specification. 1998. [18] David Waitzman, SE Deering, and Craig Partridge. Distance vector multicast routing protocol. 1988. [19] A Ballardie. Core based trees (cbt version 2) multicast routing–protocol specification–. 1997. [20] Dan Levin, Marco Canini, Stefan Schmid, Fabian Schaffert, Anja Feldmann, et al. Panopticon: Reaping the benefits of incremental sdn deployment in enterprise networks. In USENIX ATC, 2014. [21] Cheng Jin, Cristian Lumezanu, Qiang Xu, Zhi-Li Zhang, and Guofei Jiang. Telekinesis: controlling legacy switch routing with openflow in hybrid networks. In Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research, page 20. ACM, 2015. [22] Rob Enns, Martin Bjorklund, and Juergen Schoenwaelder. Netconf configuration protocol. Network, 2011. [23] Karamjeet Kaur, Japinder Singh, and Navtej Singh Ghumman.“mininet as software defined networking testing platform. In International Conference on Communication, Computing & Systems (ICCCS, 2014. [24] Natasha Gude, Teemu Koponen, Justin Pettit, Ben Pfaff, Martín Casado, Nick McKeown, and Scott Shenker. Nox: towards an operating system for networks. ACM SIGCOMM Computer Communication Review, 38(3):105–110, 2008. [25] POX Controller, [online] http://www.noxrepo.org/pox/about-pox/. [26] Floodlight OpenFlow Controller - Project Floodlight, [online] www. projectfloodlight.org/floodlight/. [27] Ryu SDN Framework, [online] http://osrg.github.io/ryu/. [28] Jan Medved, Robert Varga, Anton Tkacik, and Ken Gray. Opendaylight: Towards a model-driven sdn controller architecture. In 2014 IEEE 15th International Symposium on, pages 1–6. IEEE, 2014. [29] Thomas R Henderson, Mathieu Lacage, and George F Riley. Network simulations with the ns-3 simulator. [30] Teerawat Issariyakul and Ekram Hossain. Introduction to network simulator NS2. Springer Science & Business Media, 2011. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/52892 | - |
dc.description.abstract | 近幾年來,隨著資料量的規模增多,大數據的時代已經到來。由於資料集過度龐大,傳統的資料分析方式已經不敷使用。Hadoop因此被開發出來對大數據進行分析,其核心方法為MapReduce,即將分析工作分割成許多小部分,並指派給資料中心內眾多個節點來平行運算處理,進而加速整體的運算速度。而在將工作指派給資料中心內眾多節點的時候,最有效率的傳遞資料之方法就是多播。
本篇論文提供一個能在資料中心下部分軟體定義網路環境下可以實行多播的架構。過往的相關研究要不只有研究純軟體定義網路架構下的多播,要不就是只有部分軟體定義網路架構但是不支援多播。本篇論文著重在如何使軟體定義網路架構下的多播可行,並對這種情況下的網路壅塞進行處理。 為了使多播可行,支援軟體定義網路的交換器必須能夠以傳統多播協定與傳統交換器進行溝通。本篇論文使用「獨立組播協議-稀疏模式」做為傳統多播協定,並且以「虛擬區域網」設定做為控制多播樹的方法。當發生交通壅塞時,使用一個貪婪演算法去選擇有最大可能流量的路徑去建構多播樹。如此並不用將全部網路設備更換為支援軟體定義網路的交換器,仍然可以獲得軟體定義網路所提供的好處。 | zh_TW |
dc.description.abstract | Big data is becoming more and more popular between researchers and business developments nowadays. With high volume, high velocity, and high variety information, it requires new forms of processing rather than traditional data processing applications.
Hadoop is a widely used framework for with big data, and MapReduce is the programming model for processing large data sets with a parallel, distributed algorithm on a data center. It splits files or jobs into many parts and distributes them to the nodes in the data center to process in a parallel way, allowing data processing to be faster than conventional data processing. One way to efficiently distribute data to nodes in the data center is multicast. This thesis presents an architecture for data center multicast in a hybrid Software Defined Networking (SDN) environment, and propose an algorithm that dynamically changes the multicast tree when congestion happens. Prior works had proposed either multicast in a full SDN environment or an architecture for unicast for hybrid SDN environment. This thesis focus on how to enable multicast in a hybrid SDN environment and how to deal with congestion in this environment. To enable multicast in hybrid SDN environment, SDN switches has to use traditional multicast protocol to interact with traditional switches. In this thesis, it uses PIM-SM as the traditional, and VLAN setting for changing multicast tree. When congestion is detected, a greedy algorithm is used that chooses the path that has the maximum possible bandwidth to build a multicast tree. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T16:32:40Z (GMT). No. of bitstreams: 1 ntu-104-R02944039-1.pdf: 1132852 bytes, checksum: 4641e85b0557c7e2049cc05b937dd05e (MD5) Previous issue date: 2015 | en |
dc.description.tableofcontents | 口試委員會審定書 1
致謝 2 中文摘要 3 Abstract 4 Contents 6 List of Figures 8 1 Introduction 1 1.1 Motivation, Challenge, and Contribution 4 2 Background and Related Works 5 2.1 Difference between SDN switches and traditional switches 5 2.2 Data Center Topology and Multicast Protocols 7 2.3 Multicast using Software Defined Networking 8 2.4 Hybrid SDN Design 8 3 Architecture 10 3.1 Network Model 10 3.1.1 Notations 11 3.1.2 Constraints 12 3.1.3 Satisfaction 13 3.2 Packet Forwarding 14 3.2.1 Select Protocol From Traditional Multicast Protocols 14 3.2.2 More About PIM-SM 15 3.2.3 How to build and change multicast trees 16 3.3 System Framework 16 4 Algorithm Design 18 4.1 Switch Deployment Strategies 18 4.2 Compute multicast trees 20 5 Evaluation 24 5.1 Simulators 24 5.2 Environment Settings 25 5.3 Results 26 5.3.1 Comparison in Different Ratio of SDN Switches 26 5.3.2 Comparison in Different Number of Multicast Groups 29 5.3.3 Comparison in Situation of Dynamic Join/Leave 31 5.3.4 Comparison in Two Design Way of Hybrid SDN 32 5.3.5 Time Spent and Control Overhead when Changing Trees 33 6 Conclusion 35 Bibliography 36 | |
dc.language.iso | en | |
dc.title | 資料中心基於軟體定義網路及部分軟體定義網路架構下之多播 | zh_TW |
dc.title | Data Center Multicast in SDN and Partial SDN Environment | en |
dc.type | Thesis | |
dc.date.schoolyear | 103-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蕭旭君(Hsu-Chun Hsiao),林俊宏,吳曉光,蔡子傑 | |
dc.subject.keyword | 資料中心,多播,軟體定義網路,部分軟體定義網路,壅塞, | zh_TW |
dc.subject.keyword | data center,multicast,software defined networking,SDN,hybrid SDN,congestion, | en |
dc.relation.page | 39 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2015-08-13 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
顯示於系所單位: | 資訊網路與多媒體研究所 |
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ntu-104-1.pdf 目前未授權公開取用 | 1.11 MB | Adobe PDF |
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